Ernesto Urbaez | Engineering | Research Excellence Award

Published on by Global Academic Awards

Research Excellence Award

Ernesto Urbaez
Virginia Tech, United States
Ernesto Urbaez
Affiliation Virginia Tech
Country United States
Scopus ID mhBCpBoAAAAJ
Documents 22
Citations 88
h-index 5
Subject Area Engineering
Event Global Academic Awards
ORCID 0009-0004-8646-972X

Ernesto Urbaez of Virginia Tech has demonstrated sustained engagement in engineering-related investigations supported by peer-reviewed publications, citation performance, and interdisciplinary technical contributions. His academic profile reflects participation in contemporary engineering research areas and scholarly dissemination through indexed publications.[1]

Abstract

This academic article summarizes the research profile and scholarly contributions of Ernesto Urbaez in the field of engineering. The profile is characterized by peer-reviewed publications, measurable citation activity, and participation in technically oriented research initiatives. With documented scholarly output and an emerging citation footprint, the researcher demonstrates active engagement in engineering sciences and interdisciplinary technological inquiry. The recognition under the Research Excellence Award category reflects academic consistency, publication quality, and contribution to research dissemination within the global academic community.[1]

Keywords

Engineering Research, Academic Recognition, Scholarly Publications, Citation Metrics, Research Excellence Award, Virginia Tech, Technical Innovation, Interdisciplinary Engineering, Research Impact, Scholarly Contribution

Introduction

Engineering research plays a significant role in advancing scientific understanding, industrial innovation, and applied technological development. Academic recognition programs such as the Research Excellence Award evaluate researchers based on publication performance, citation influence, research quality, and broader scholarly engagement. Ernesto Urbaez has contributed to the engineering domain through publications and collaborative academic activities associated with Virginia Tech. The documented metrics associated with the researcher indicate sustained participation in scholarly communication and research dissemination.[2]

Research evaluation frameworks commonly consider indicators such as the number of indexed documents, citation counts, and h-index values to assess scholarly productivity and influence. These metrics provide insight into the visibility and academic reach of published work while also supporting comparative analysis within related scientific disciplines.[3]

Research Profile

Ernesto Urbaez is affiliated with Virginia Tech in the United States and has established a research profile centered on engineering-oriented investigations and scholarly publication activity. The researcher has accumulated 22 documented publications and 88 citations, resulting in an h-index of 5. These indicators suggest a developing yet academically visible research trajectory within engineering sciences.[1]

The academic profile demonstrates engagement with technical methodologies, engineering analysis, and interdisciplinary collaboration. Citation activity associated with the publications indicates that the researcher’s work has received measurable scholarly attention within the broader scientific community.[2]

  • Affiliation with Virginia Tech and participation in engineering-related academic research.
  • Documented scholarly output consisting of indexed publications and citation activity.
  • Contribution to interdisciplinary engineering investigations and technical dissemination.
  • Recognition within academic evaluation frameworks through citation-based indicators.

Research Contributions

The research contributions associated with Ernesto Urbaez reflect participation in engineering scholarship through technical publications and collaborative academic studies. The body of work contributes to the dissemination of engineering knowledge and supports the advancement of applied scientific inquiry. The publications collectively indicate involvement in analytical problem-solving, engineering methodologies, and technical evaluation processes.[4]

Research activity in engineering frequently involves integration of theoretical modeling, applied experimentation, and computational evaluation. The scholarly contributions attributed to the researcher align with these broader academic practices and demonstrate engagement with evolving engineering challenges and technological frameworks.[5]

  • Participation in peer-reviewed engineering research publications.
  • Engagement with interdisciplinary technical investigations and collaborative studies.
  • Contribution to scientific communication and academic dissemination.
  • Support for engineering innovation through scholarly inquiry and analytical research.

Publications

The publication profile of Ernesto Urbaez demonstrates active participation in engineering scholarship and academic communication. The documented publication count reflects continued research productivity and involvement in technical dissemination channels indexed within recognized scholarly databases.[1]

  1. Engineering-related peer-reviewed publications indexed through scholarly databases.
  2. Collaborative technical studies involving analytical and interdisciplinary methodologies.
  3. Research dissemination through conference papers and academic communication channels.
  4. Contributions to applied engineering and technology-oriented investigations.

Representative DOI-linked academic references associated with engineering scholarship include publications addressing analytical modeling, computational engineering, and interdisciplinary research methodologies.[6]

Research Impact

Research impact is frequently evaluated through citation performance, publication visibility, and broader academic influence. Ernesto Urbaez has achieved 88 citations with an h-index of 5, indicating that portions of the researcher’s published work have received consistent scholarly acknowledgment. These metrics suggest growing recognition within engineering-related academic discussions and technical literature.[3]

Citation indicators should be interpreted within the broader context of discipline-specific publication practices, collaboration networks, and research timelines. Nevertheless, the available metrics demonstrate evidence of measurable engagement from the academic community and reflect the relevance of the researcher’s contributions within engineering scholarship.[4]

Award Suitability

The Research Excellence Award recognizes researchers demonstrating scholarly consistency, technical contribution, and measurable academic engagement. Ernesto Urbaez’s profile aligns with several criteria commonly associated with academic recognition programs, including peer-reviewed publication activity, citation-based visibility, and participation in engineering research initiatives.[5]

The combination of indexed publications, citation metrics, and institutional affiliation with Virginia Tech supports the researcher’s suitability for recognition under the Research Excellence Award category. The profile reflects continued participation in scientific inquiry and contribution to the dissemination of engineering knowledge through scholarly communication.[2]

Conclusion

Ernesto Urbaez has developed a scholarly profile characterized by engineering-related research activity, peer-reviewed publication output, and measurable citation performance. The academic indicators associated with the researcher demonstrate engagement with technical inquiry and interdisciplinary engineering scholarship. Recognition through the Research Excellence Award category reflects the researcher’s contributions to scientific dissemination and ongoing participation within the academic research community.[1]

References

  1. Google Scholar. (n.d.). Scholar profile details: Ernesto Urbaez, Author ID mhBCpBoAAAAJ. Google Scholar.

    https://scholar.google.com/citations?user=mhBCpBoAAAAJ&hl=en&inst=13410158990364976897
  2. Pilot Study to Incorporate Network-Level Structural Condition in Agency Pavement Management Practices.
    https://journals.sagepub.com/doi/10.1177/03611981241252152
  3. Calibration of a 3D-FE Model with Non-Contact Laser Doppler Vibrometer (LDV) Measurements of Pavement Deflection Velocity Under Accelerated Pavement Testing

    https://www.mdpi.com/2076-3417/16/10/4611
  4. Cracking performance evaluation of BMD surface mixtures with conventional and high RAP contents: insights from accelerated pavement testing program
    doi.org/10.1080/10298436.2026.2620548
  5. Methodology to Validate Traffic Speed Deflection Devices (TSDDs) Measurements Using Laser Doppler Vibrometers (LDV) Sensors
    https://vtechworks.lib.vt.edu/items/057248d4-1094-453d-b197-f023494f73b1
  6. Crossref. (n.d.). Estimation of the” C” value considered In the AASHTO-93 guide for back analysis of the elastic modulus of the subgrade. Crossref.
    https://trid.trb.org/View/1143765

Jiqing Wang | Engineering | Research Excellence Award

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Dr. Jiqing Wang | Engineering | Research Excellence Award

Beihang University School of Electronic and Information Engineering | China

Dr. Jiqing Wang is an emerging researcher in electronic science and intelligent computing, specializing in high-efficiency deep neural network acceleration and hardware–software co-design. His work bridges algorithm optimization—including model quantization, separable and partial convolution, and multi-scale feature extraction—with RTL-level FPGA/SoC hardware implementations. He has contributed to peer-reviewed, Scopus-indexed research, notably on hardware-friendly joint denoising and demosaicing systems that reduce model complexity while enhancing image quality and computational efficiency. With 29 citations across 24 documents and an h-index of 4, his research demonstrates growing impact in edge AI, computer vision acceleration, and reconfigurable hardware architectures, aligning with early-stage Research Excellence recognition.

Citation Metrics (Scopus)

30

25

20

15

10

5

0

Citations
29

Documents
7

h-index
4

■ Citations
■ Documents
■ h-index


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Don State Technical University | Russia

Assoc. Prof. Dr. Anastasia Feofilova is an accomplished researcher in intelligent transport systems, traffic flow prediction, and urban mobility engineering. Her work focuses on advanced AI-driven traffic modeling, including hybrid CNN–LSTM/GRU architectures, attention mechanisms, geoinformation systems in transport logistics, cooperative intelligent transport systems (C-V2X), and the impacts of autonomous vehicles on road network efficiency. She has contributed to peer-reviewed journals and international book chapters, with research published in reputable outlets such as Smart Cities, Sensors, Applied and Computational Engineering, and E3S Web of Conferences. With an established Scopus profile, consistent citation impact, interdisciplinary collaborations, and contributions to software development and educational-methodological outputs, her research demonstrates both scientific rigor and applied societal relevance, particularly in smart city development and road safety enhancement.

Citation Metrics (Scopus)

40

30

20

10

0

Citations
36

Documents
7

h-index
4

■ Citations
■ Documents
■ h-index

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Prof. Dr. Gennaro Trancone | Engineering | Innovative Research Award

University of Naples Federico II | Italy

Prof. Dr. Gennaro Trancone is an environmental engineer and researcher whose work spans anaerobic digestion, dark fermentation, biofilm reactor design, biogas optimization, and circular bioeconomy strategies, with strong expertise in asbestos remediation, construction waste valorization, and marine environmental monitoring. His research contributions include advances in renewable biogas production from food waste, optimization of chemical treatments for biomass-based adsorbents, the use of dark fermentation–derived organic acids for concrete waste processing, and integrated chemical–ecotoxicological assessments for marine-coastal systems. He has also explored sediment washing for arsenic removal, environmental implications of micro- and nano-plastics in asphalt materials, and the mobility of toxic elements in foreshore sediments. With 155 citations, 9 published documents, and an h-index of 7, his publications in leading international journals highlight his significant role in environmental biotechnology, sustainable waste management, and the development of eco-innovative solutions for pollution prevention and resource recovery.

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Bounaas, M., Haouichi, M., Gattal, B., Hamza, W., Benalia, A., Derbal, K., Benzina, M., Pizzi, A., Trancone, G., & Panico, A. (2025). Optimization of NaOH chemical treatment parameters for biomass-based adsorbents in cationic dye removal. Processes.

Achouri, O., Bianco, F., Trancone, G., & Race, M. (2025). A critical review of anaerobic biofilm reactors for the renewable biogas production from food waste. Journal of Environmental Chemical Engineering.

Trancone, G., Policastro, G., Spasiano, D., Race, M., Parrino, F., Fratino, U., Fabbricino, M., & Pirozzi, F. (2025). Treatment of concrete waste from construction and demolition activities: Application of organic acids from continuous dark fermentation in moving bed biofilm reactors. Chemical Engineering Journal.

Ferraro, A., Marino, E., Trancone, G., Race, M., Mali, M., Pontoni, L., Fabbricino, M., Spasiano, D., & Fratino, U. (2023). Assessment of environmental parameters effect on potentially toxic elements mobility in foreshore sediments to support marine-coastal contamination prediction. Marine Pollution Bulletin.

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Jinyou Kang | Engineering | Best Researcher Award

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Assist. Prof. Dr. Jinyou Kang | Engineering | Best Researcher Award

Yanshan University | China

Assist. Prof. Dr. Jinyou Kang is a promising researcher in the field of mechanical engineering, currently affiliated with the Key Laboratory of High Efficiency and Clean Mechanical Manufacture, Jinan. His research focuses on intelligent manufacturing, mechanical vibration control, and high-efficiency machining technologies, particularly in the study and optimization of circular saw blade dynamics, wear behavior, and noise mitigation. Assist. Prof. Dr. Jinyou Kang has published 7 SCI-indexed papers as the sole first author in top-tier journals such as Mechanical Systems and Signal Processing, International Journal of Mechanical Sciences, and Journal of Materials Processing Technology, with the majority ranked in JCR Q1. His works advance understanding of tool wear mechanisms, FEM-based modeling, vibration suppression, and green manufacturing processes, contributing to both theoretical insights and industrial applications. With over 106 citations, multiple patents, and provincial science and technology awards.

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1. Kang, J., Zhang, J., Zhang, H., Yuan, X., Lv, C., & Bai, T. (2025). A laminated-core circular sawblade with built-in cavities for improving machinability. International Journal of Mechanical Sciences, 110148.

2. Zuo, C., Zhang, H., Kang, J., Zhang, J., Wang, J., & Guo, C. (2025). Damage characteristics and material removal mechanisms of SSiC scratched by diamond grits: Comparison with RB-SiC. Ceramics International.

3. Bai, T., Wang, X., Gao, Z., Wang, S., Zuo, C., Kang, J., Zhang, H., & Zhang, J. (2025). Tool wear analysis of high-speed sawing of aerospace aluminum alloy based on FEM simulation and cutting experiments. Journal of Manufacturing Processes.

4. Kang, J., Zhang, H., Zhang, J., Yuan, X., Lv, C., Bai, T., Gong, Y., & Guo, J. (2025). Development of a novel circular saw blade substrate with high stiffness for mitigating vibration noise and improving sawing performance. Mechanical Systems and Signal Processing, 111934.

5. Kang, J., Zhang, H., Zhang, J., Bai, T., Zhang, Z., Guo, J., Gong, Y., & Niu, P. (2025). Wear analysis of teeth for roughing and finishing in the high-efficiency machining of hard alloys using carbide circular saw blades. Engineering Failure Analysis, 108983.

Ramar Azhagu | Fluid Dynamics | Best Researcher Award

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Dr. Ramar Azhagu | Fluid Dynamics | Best Researcher Award

Chennai Institute of Technology | India

Dr. Ramar Azhagu, is a dedicated mathematician specializing in Fluid Dynamics, with a doctoral research titled “An Investigation on Heat and Mass Transfer through Carreau Fluid” from Hindusthan College of Arts and Science, Bharathiar University, Coimbatore. Currently serving as an Assistant Professor at Chennai Institute of Technology, he has extensive teaching experience across multiple engineering colleges since 2009, demonstrating excellence in pedagogy and academic mentorship. Dr. Ramar Azhagu has contributed to the field through publications in reputed journals on MHD Carreau fluids, Maxwell fluids, and applications of machine learning in fluid mechanics, with 15 citations, 3 documents, and an h-index of 2, reflecting his growing scholarly impact. His active participation in international conferences, workshops, webinars, and faculty development programs underscores his commitment to continuous learning and knowledge dissemination. With strong research, teaching, and interdisciplinary expertise, Dr. Ramar Azhagu is poised to make significant contributions as an Associate Professor in Mathematics.

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Ramar, A., Arulmozhi, A., Balamuralitharan, S., Khan, I., Hajjej, F., … (2024). Melting heat effect in MHD flow of Maxwell fluid with zero mass flux. Case Studies in Thermal Engineering, 53, 103910.

Ramar, A., Sudarmozhi, S. K., Selvi, P. D., Benabdallah, F., Batool, N., … (2025). Radiative flow of hybrid nanofluid (TiO₂ + Ag/Blood and Au + Al₂O₃/Blood) over a sheet with Cattaneo–Christov heat transport. Journal of Radiation Research and Applied Sciences, 18(4), 101930.

Ramar, A., Sudarmozhi, K., Selvi, P. D., Akanni, J. O., … (2025). Numerical analysis of hybrid nanofluid flow over a sheet with Cattaneo-Christov heat flux model. Modeling Earth Systems and Environment, 11(5), 378.

Azhagu Ramar, N. M. K., Bhuvaneswari, E., Nirmalkumar, R., Abhilash, P., Kalyan, M., … (2025). Influence of Soret and Dufour impacts on Casson fluid flow in a channel embedded in a porous medium. Advances in Nonlinear Variational Inequalities, 28(1s).

Gayathri, D., & Azhagu Ramar, A. (2024). Sign language recognition using convolutional neural network. International Journal of Intelligent Systems and Applications in Engineering, 12, 329–337.

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Assoc. Prof. Dr. Abdulaziz Almaktoom | Engineering | Best Researcher Award

Effat University | Saudi Arabia

Assoc. Prof. Dr. Abdulaziz Almaktoom, is a distinguished scholar and leader in Operations and Supply Chain Management, serving as Associate Professor and Chair of the Business Administration Department. With 39 publications, 275 citations, and an h-index of 10, he is recognized among the top 20 scientists in Decision Science and Operations Management in Saudi Arabia. His expertise spans operations management, project management, data analytics, industrial ergonomics, lean and six sigma, quality assurance, risk management, and applied statistics. He has pioneered innovative curriculum development, establishing specialized programs and securing full accreditation from NCAAA and AACSB. Renowned for mentoring students, leading cross-functional teams, and driving industry collaborations, he combines research excellence with impactful teaching. His strategic vision has enhanced academic standards, tripled student enrollment, and supported students’ success, while his consultancy and professional certifications underscore his commitment to advancing operational efficiency, research innovation, and applied solutions across industry and academia.

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Merabet, A., Saighi, A., Saad, H., Ferradji, M. A., Laboudi, Z., & Almaktoom, A. T. (2025). AI for colon cancer: A focus on classification, detection, and predictive modeling. International Journal of Medical Informatics, 106115.

Almaktoom, A. T., & Yusuf, N. (2025). Optimizing forecasting techniques for cost-effective procurement of controlled medications in Saudi Arabia’s healthcare system. International Journal of Pharmaceutical and Healthcare Marketing.

Almaktoom, A. T. (2025). Resilience modeling of mobile service for quality assurance. Operations Management Research, 18(1), 182–194.

Sasikumar, A., Ravi, L., Devarajan, M., Selvalakshmi, A., & Almaktoom, A. T. (2024). Corrections to “Blockchain-Assisted Hierarchical Attribute-Based Encryption Scheme for Secure Information Sharing in Industrial Internet of Things.” IEEE Access, 12, 163197–163197.

Bezoui, M., Kermali, A., Bounceur, A., Qaisar, S. M., & Almaktoom, A. T. (2024). Deep reinforcement learning for multiobjective scheduling in Industry 5.0 reconfigurable manufacturing systems. In Machine Learning for Networking: 6th International Conference, MLN 2023

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Dr. Qing Lyu | Engineering | Best Researcher Award

Wake Forest University School of Medicine | United States

Dr. Qing Lyu is a highly accomplished researcher in biomedical engineering and AI-driven medical imaging, with a strong track record of innovation and scholarly impact. He holds a B.S. and M.S. in Biomedical Engineering from Shanghai Jiao Tong University and a Ph.D. from Rensselaer Polytechnic Institute, where his dissertation focused on deep neural networks for MRI applications. Currently, he serves as Assistant Professor in Radiology and Adjunct Assistant Professor in Biomedical Engineering at Wake Forest University School of Medicine. Dr. Qing Lyu’s research spans MRI and CT super-resolution, multimodal radiomics, deep learning for disease prediction, and AI-based clinical translation. His scholarly output includes 14 documents indexed in Scopus, accruing 594 citations and an h-index of 8, reflecting both quality and influence. He holds multiple patents, has secured competitive grants, and serves on editorial boards while reviewing for top journals and conferences, underscoring his leadership in advancing biomedical imaging, AI, and translational medical research.

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Lyu, Q., Tan, J., Zapadka, M. E., Ponnatapura, J., Niu, C., Myers, K. J., Wang, G., … & Whitlow, C. (2023). Translating radiology reports into plain language using ChatGPT and GPT-4 with prompt learning: Results, limitations, and potential. Visual Computing for Industry, Biomedicine, and Art, 6(1), 9.

Lyu, Q., Shan, H., Steber, C., Helis, C., Whitlow, C., Chan, M., & Wang, G. (2020). Multi-contrast super-resolution MRI through a progressive network. IEEE Transactions on Medical Imaging, 39(9), 2738–2749.

Lyu, Q., Shan, H., & Wang, G. (2020). MRI super-resolution with ensemble learning and complementary priors. IEEE Transactions on Computational Imaging, 6, 615–624.

Lyu, Q., & Wang, G. (2022). Conversion between CT and MRI images using diffusion and score-matching models. arXiv preprint arXiv:2209.12104.

Niu, C., Li, M., Fan, F., Wu, W., Guo, X., Lyu, Q., & Wang, G. (2022). Noise suppression with similarity-based self-supervised deep learning. IEEE Transactions on Medical Imaging, 42(6), 1590–1602.

Yuh-Ming Ferng | Engineering | Best Researcher Award

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Prof. Yuh-Ming Ferng | Engineering | Best Researcher Award

National Tsing Hua University | Taiwan

Prof. Yuh-Ming Ferng, a distinguished Professor at the Department of Engineering and System Science, Institute of Nuclear Engineering and Science, National Tsing Hua University (NTHU), has made significant contributions to nuclear engineering through his extensive research and academic leadership. He earned his B.S. and Ph.D. in Nuclear Engineering from NTHU, where his doctoral thesis focused on the numerical simulation of the rewetting process. With a professional career spanning over three decades, Prof. Yuh-Ming Ferng has held roles as Assistant, Associate, and Full Professor at NTHU, alongside senior research positions at its Nuclear Science and Technology Development Center and the Center for Energy and Environmental Research, as well as the Institute of Nuclear Energy Research. His research expertise covers nuclear reactor safety, severe accident analysis, CFD turbulence modeling, two-phase flow, thermal management, fuel cell simulation, and renewable energy systems. With 2,470 citations, 168 documents, and an h-index of 30, he is a highly impactful researcher in his field.

Profile: Scopus

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  • Ferng, Y.-M., & co-authors. (2026). Determining minimum site area for deep geological repository of spent fuels using thermal simulations. Annals of Nuclear Energy. Advance online publication.

  • Ferng, Y.-M., & co-authors. (2025). Thermal management design for the Be target of an accelerator-based boron neutron capture therapy system using numerical simulations with boiling heat transfer models. Processes. Advance online publication.

  • Ferng, Y.-M., & co-authors. (2024). Development of thermal-hydraulic coupling model for deep-geological disposal of high-level radioactive wastes. Nuclear Engineering and Design.

  • Ferng, Y.-M., & co-authors. (2024). Numerical model for noise reduction of small vertical-axis wind turbines. Wind Energy Science.

  • Ferng, Y.-M., & co-authors. (2024). Numerical prediction of the aerodynamics and aeroacoustics of a 25 kW horizontal axis wind turbine. Journal of Mechanics.

Xun Zhang | Engineering | Best Researcher Award

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Mr. Xun Zhang | Engineering | Best Researcher Award

ISEP | France

Mr. Xun Zhang is a distinguished scholar specializing in embedded systems and wireless communication, currently serving as Professor at ISEP and permanent researcher at Saclay-Versailles University. He earned his MSc from Sorbonne University in 2005, PhD in Electrical Engineering from the University of Lorraine in 2009, and completed his Thesis Habilitation in Optical Wireless Communication at Sorbonne University in 2021. His career includes appointments as visiting professor at Tsinghua University, China, and De Vic University, Spain, along with postdoctoral research at Centralesupélec, Rennes. A senior member of IEEE, he has contributed extensively to the academic community as Associate Editor of IEEE Transactions on Broadcasting, Guest Editor for MDPI Sensors, Editor-in-Chief of the International Journal of Internet of Things, and organizer of major IEEE conferences including BMSB and ISCAS. He has supervised numerous postdoctoral researchers and PhD students on cutting-edge topics such as visible light communication, 6G IoT networks, indoor localization, and AI-driven optical systems. Recognized with awards including the Vivatech Innovation Award and supported by a French government PhD scholarship, his research continues to shape the future of IoT, 5G/6G, and optical communication technologies.

Profile: Google Scholar

Featured Publications

Ding, W., Yang, F., Yang, H., Wang, J., Wang, X., Zhang, X., & Song, J. (2015). A hybrid power line and visible light communication system for indoor hospital applications. Computers in Industry, 68, 170–178.

Song, J., Ding, W., Yang, F., Yang, H., Wang, J., Wang, X., & Zhang, X. (2014). Indoor hospital communication systems: An integrated solution based on power line and visible light communication. In 2014 IEEE Faible Tension Faible Consommation (FTFC) (pp. 1–6). IEEE.

Shi, L., Shi, D., Zhang, X., Meunier, B., Zhang, H., Wang, Z., Vladimirescu, A., Li, W., … (2020). 5G Internet of radio light positioning system for indoor broadcasting service. IEEE Transactions on Broadcasting, 66(2), 534–544.

Kaloxylos, A., Gavras, A., Camps Mur, D., Ghoraishi, M., & Hrasnica, H. (2021). AI and ML–Enablers for beyond 5G networks. IEEE Communications Standards Magazine, 5(2), 12–18.

Malik, B., & Zhang, X. (2015). Solar panel receiver system implementation for visible light communication. In 2015 IEEE International Conference on Electronics, Circuits, and Systems (ICECS) (pp. 249–252). IEEE.